Fault Diagnosis of Landing Gear Expert System Based on Neural Network

The correct diagnosis of the fault degree of aircraft landing gear hydraulic retraction system can help pilots take timely actions to deal with different degrees of failure and avoid personnel and property losses. The purpose of this paper is to propose a kind of growing expert system based on past data by combining with neural network. This paper establishes the simulation model of a certain type of aircraft landing gear hydraulic retraction system and implants different degrees of fault, extracts fault data, normalizes the fault data and trains the corresponding neural network model. The expert system extracts the number of abnormal sensor in the fault data through the neural network, and compares it with the database in the expert system, so that the fault type of the aircraft landing gear hydraulic retraction system can be effectively diagnosed.